Samantha N.

Key Skills

Software

Telus

Mercor

Label Studio

Other

Top Subject Matter

Data science- organization and trend evaluation.

Computer science- programming and machine learning

Health- Data organization and sorting

Top Data Types

Image

Video

Audio

Top Task Types

Bounding Box

Segmentation

Question Answering

Classification

Transcription

Evaluation/Rating

Computer Programming/Coding

Data Collection

Prompt + Response Writing (SFT)

Text Generation

Text Summarization

Freelancer Overview

I have professional experience in data annotation, data labeling, and AI training data projects, having worked with leading organizations including RWS, Telus International, and MeCor AI. In 2025, I contributed to RWS's Diamond Project, where I specialized in bounding box annotation for computer vision datasets, accurately identifying and labeling objects to support AI-powered object detection models. I also worked on the Hedgehog Project through Handshake, performing data evaluation, annotation, and quality assurance tasks to improve the performance and reliability of machine learning systems. Additionally, I gained valuable data labeling experience with Telus International (2023) and MeCor AI (2026), where I annotated and reviewed datasets while ensuring compliance with project guidelines and quality standards. My key strengths include exceptional attention to detail, strong analytical skills, and the ability to maintain high accuracy across large-scale annotation projects. I am experienced in following complex annotation guidelines, conducting quality control reviews, and delivering consistent results within remote, fast-paced environments. My background across multiple AI training and data labeling projects has equipped me with a solid understanding of machine learning data preparation, data quality management, and the critical role accurate annotations play in developing reliable AI systems.

Labeling Experience

Data Annotation and labeling

TextSegmentation

On the Hedgehog Project through Handshake (2025), I worked on audio segmentation tasks designed to support the training and improvement of speech recognition and language-processing AI models. My primary responsibility was to carefully review audio recordings and divide them into accurate segments based on speech boundaries, speaker changes, pauses, and other predefined annotation guidelines. This required close attention to detail, strong listening skills, and the ability to consistently identify relevant audio events while maintaining high-quality annotation standards. In addition to segmenting audio files, I performed quality assurance checks to ensure that annotations were accurate, consistent, and aligned with project requirements. I worked with diverse audio datasets containing varying accents, speech patterns, and recording conditions, helping create structured training data for machine learning systems. Through this project, I strengthened my skills in audio annotation, data quality management, guideline interpretation, and AI training data preparation, while consistently meeting productivity and accuracy targets in a remote work environment.

2025 - 2026

Data labeling- Expert level

ImageBounding Box

I worked as a Data Annotator specializing in bounding box annotation for computer vision and machine learning applications. My responsibilities included accurately identifying and labeling objects within images by drawing precise bounding boxes around target items according to detailed project guidelines. I conducted quality checks to ensure annotation consistency, maintained high accuracy standards, and collaborated within a remote team environment to support the development and training of AI models used for object detection and image recognition tasks.

2025 - 2026

Education

Work History